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7th Edition Global Conference on Wireless and Optical Technologies, GCWOT 2024

作者： Ali, Sara Naz, Bushra Narejo, Sanam Ali, Sahil Pabani, Jitander Kumar Mehran University of Engineering and Technology National Center of Robotics and Automation Cms Lab Jamshoro Pakistan Mehran University of Engineering and Technology Department of Computer Systems Engineering Jamshoro Pakistan Mehran University of Engineering and Technology National Center of Rorotics and Automation Cms Lab Jamshoro Pakistan Dawood University of Engineering and Technology Department of Telecommunication Engineering Karachi Pakistan

ISBN: (纸本)9798331534271

The fast growth of digital communication via smartphones and social media has made textual data as one of the most essential forms of people's expressions. Accurate emotion discovery from text is thus important for applications in customer sentiment analysis and interactive technologies, be it a web, desktop, or mobile application, an intelligent robot, or minor connected devices. This paper is intended to evaluate the performance of five state-of-the-art transformer models, including BERT, ALBERT, DistilBERT, Transformer XL, and RoBERTa, for multiclass emotion detection using the IEMOCAP dataset. From the results, it is observed that DistilBERT has the highest accuracy of 79.2%, implying an effective approach in balancing model size and performance. These research show that smaller models like DistilBERT often outperform larger models by reducing their overfitting and computational demands. The findings also highlights the need for task-specific fine-tuning and optimization in emotion detection. © 2024 IEEE.

关键词： DistilBERT IEMOCAP NLP Text Emotion Detection Transformers

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Cascade LTI System for Acoustic Emission Digital Signal Processing: Result Visualization via Scalogram for Defect Pattern Representation

Cascade LTI System for Acoustic Emission Digital Signal Proc...

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Digital Signal Processing and its Applications (DSPA), International Conference on

作者： Yeldos A. Altay Alexey V. Fedorov Department of Robotics and Technical Means of Automation Satbayev University Almaty Kazakhstan Faculty of Control Systems and Robotics ITMO University Saint-Petersburg Russian Federation

ISBN: (数字)9798331518752

ISBN: (纸本)9798331518769

Modern acoustic emission (AE) diagnostic systems are sensitive instruments for detecting developing defects. A significant limitation of the AE method is the difficulty of isolating signals against the background of interference, which significantly reduces the signal-to-interference ratio. Therefore, in this article a cascade filtering scheme for visualizing acoustic signatures through a scalogram is proposed to isolate AE signals that characterize the process of defect formation. Acoustic portraits of the isolated signals characterizing the process of defect formation are given. It is shown that the amplitude of the AE signal from a defective structure during crack formation is characterized by the highest values of the signal amplitude and has a rich frequency-time structure, the signal shape of which is determined by discrete AE.

关键词： Linear systems Visualization Time-frequency analysis Filtering Shape Instruments Interference Digital signal processing Acoustic emission Signal to noise ratio

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Augmented Reality-based Robot Control for Laparoscopic Surgery

Augmented Reality-based Robot Control for Laparoscopic Surge...

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作者： Kunz, Christian Maierhofer, Pascal Gyenes, Balázs Franke, Nikolai Younis, Rayan Müller-Stich, Beat-Peter Wagner, Martin Mathis-Ullrich, Franziska Health Robotics and Automation Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Karlsruhe76131 Germany Department for General Visceral and Transplantation Surgery Heidelberg University Hospital Heidelberg69120 Germany

Minimally invasive surgery is the standard for many abdominal interventions, with an increasing use of telemanipulated robots. As collaborative robots enter the field of medical interventions, their intuitive control needs to be addressed. Augmented reality can thereby support a surgeon by representing the surgical scene in a natural way. In this work, an augmented reality based robot control for laparoscopic cholecystectomy is presented. A user can interact with the virtual scene to clip the cystic duct and artery as well as to manipulate the deformable gallbladder. An evaluation was performed based on the SurgTLX and system usability scale. © 2022 by Walter de Gruyter Berlin/Boston.

关键词： Augmented reality

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Lidar-Visual-Inertial Odometry with Online Extrinsic Calibration

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Journal of Shanghai Jiaotong university(Science) 2023年第1期28卷 70-76页

作者：茅天阳赵文韬王景川陈卫东 Department of Automation Institute of Medical RoboticsShanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai 200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240China

To achieve precise localization,autonomous vehicles usually rely on a multi-sensor perception system surrounding the mobile *** is a time-consuming process,and mechanical distortion will cause extrinsic calibration ***,we propose a lidar-visual-inertial odometry,which is combined with an adapted sliding window mechanism and allows for online nonlinear optimization and extrinsic *** the adapted sliding window mechanism,spatial-temporal alignment is performed to manage measurements arriving at different *** nonlinear optimization with online calibration,visual features,cloud features,and inertial measurement unit(IMU)measurements are used to estimate the ego-motion and perform extrinsic *** experiments were carried out on both public datasets and real-world *** indicate that the proposed system outperforms state-of-the-art open-source methods when facing challenging sensor-degenerating conditions.

关键词： autonomous vehicles multi-sensor fusion online calibration

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Research on Transformer Partial Discharge Localization Based on Residual Neural Network Model 43

Research on Transformer Partial Discharge Localization Based...

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43rd Chinese Control Conference, CCC 2024

作者： Li, Shilong Li, Ang Zhang, Jianlei Zhang, Chunyan Nankai University College of Artificial Intelligence Department of Automation Tianjin300071 China Nankai University Tianjin Key Laboratory of Intelligent Robotics Tianjin300071 China Nankai University College of Artificial Intelligence Tianjin China

ISBN: (纸本)9789887581581

In the monitoring of electrical insulation, the detection of partial discharge (PD) activity is crucial to ensure the uninterrupted operation of power systems. The occurrence of PD is closely related to the weakening of insulation strength, and a failure to inspect PD occurrences may lead to unforeseen insulation breakdowns. A comprehensive PD diagnostic process involves the detection, localization, and classification of PD. Accurate localization of the source of partial discharge is essential for identifying weakened insulation segments. The conventional method for localization is based on the Time Difference of Arrival (TDOA), which is highly sensitive to delay estimation and often computationally intensive. Here we propose a data-driven approach based on a residual neural network model. It utilizes CST electromagnetic simulation software to simulate real-sized transformers and employs ultra-high-frequency sensors to measure field strength intensity as the network input. The output corresponds to the coordinates of the PD source and is used for network training. Simulation results demonstrate that this method exhibits high localization accuracy and efficiency. Moreover, different network models and datasets are considered for their influence on localization results, setting the groundwork for a more reliable PD source localization. © 2024 Technical Committee on Control Theory, Chinese Association of automation.

关键词： Partial discharges

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Smooth Surface-to-Surface Contact Control for Rope-Base Soft-Tip Manipulator

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IEEE Transactions on automation Science and Engineering 2025年 22卷 16297-16308页

作者： Guangli Sun Fangxun Zhong Peng Li Linzhu Yue Zhi Chen Xiang Li Yun-Hui Liu Department of Mechanical and Automation Engineering T Stone Robotics Institute The Chinese University of Hong Kong Shatin SAR Hong Kong School of Science and Engineering The Chinese University of Hong Kong Shenzhen China School of Mechanical Engineering and Automation Harbin Institute of Technology at Shenzhen Shenzhen China Hong Kong Centre for Logistics Robotics SAR Hong Kong Department of Automation Tsinghua University Beijing China

A new control pipeline has been proposed for the Rope-Base Soft-tip Manipulator (RBSM) to execute the surface contact task to prevent the jamming and slipping problems. The control pipeline enables smooth surface-to-surface contact for the RBSM using only force sensors, eliminating the dependence on additional pose measurement of the window surface plane and soft-tip deformation information. The pipeline consists of three steps: free contact step implemented by an exponential force shape controller to avoid force overshoot to the window surface; orientation refinement step implemented by a force and torque combined controller to make the RBSM cleaning head surface stable adapt to the smooth window surface; and finally, a release normal force step to reduce head jamming and region covering with a pre-defined vibration-less cleaning trajectory for smooth cleaning on the slippery window surface. The proposed pipeline has been validated in a Rope base Cleaning Manipulator prototype to clean a common window surface. The force and velocity curves during the cleaning experiment show that the proposed method achieves smooth scraping and cleaning under unknown initial significant errors in surface orientation. Note to Practitioners—The current robotic rope base high-rise exterior work, especially cleaning, is not efficient due to the instability of the base and the influence of the soft-tip on the window and end-effector contact. A new control pipeline has been proposed for the Rope-Base Soft-tip Manipulator (RBSM) to clean the window surface smoothly to avoid jamming, slipping, and leaving problems in the contact process. The control pipeline realizes smooth surface-to-surface contact of RBSM with only force sensors without additional pose measurement of the window surface plane. The pipeline consists of three steps: free contact step implemented by an exponential force shape controller to avoid force overshoot to the window surface; orientation refinement step implemented

关键词： Surface cleaning Force Manipulators Robots Jamming Pipelines End effectors Trajectory Surface impedance Force sensors

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Reachability-Based Confidence-Aware Probabilistic Collision Detection in Highway Driving

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Engineering 2024年第2期33卷 90-107页

作者： Xinwei Wang Zirui Li Javier Alonso-Mora Meng Wang School of Engineering and Materials Science Queen Mary University of LondonLondon E14NSUK Department of Cognitive Robotics Delft University of TechnologyDelft 2628 CDNetherlands School of Mechanical Engineering Beijing Institute of TechnologyBeijing 100081China Chair of Traffic Process Automation “Friedrich List”Faculty of Transport and Traffic SciencesTU DresdenDresden 01069Germany

Risk assessment is a crucial component of collision warning and avoidance systems for intelligent ***-based formal approaches have been developed to ensure driving safety to accurately detect potential vehicle ***,they suffer from over-conservatism,potentially resulting in false–positive risk events in complicated real-world *** this paper,we combine two reachability analysis techniques,a backward reachable set(BRS)and a stochastic forward reachable set(FRS),and propose an integrated probabilistic collision–detection framework for highway *** this framework,we can first use a BRS to formally check whether a two-vehicle interaction is safe;otherwise,a prediction-based stochastic FRS is employed to estimate the collision probability at each future time ***,the framework can not only identify non-risky events with guaranteed safety but also provide accurate collision risk estimation in safety-critical *** construct the stochastic FRS,we develop a neural network-based acceleration model for surrounding vehicles and further incorporate a confidence-aware dynamic belief to improve the prediction *** experiments were conducted to validate the performance of the acceleration prediction model based on naturalistic highway driving *** efficiency and effectiveness of the framework with infused confidence beliefs were tested in both naturalistic and simulated highway *** proposed risk assessment framework is promising for real-world applications.

关键词： Probabilistic collision detection Confidence awareness Probabilistic acceleration prediction Reachability analysis Risk assessment

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Problems in Control Systems of Electric Drives of Metalworking Machines

Problems in Control Systems of Electric Drives of Metalworki...

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2024 Conference of Young Researchers in Electrical and Electronic Engineering, ElCon 2024

作者： Lazovskiy, Nikolay V. Kundyukov, Oleg A. Ershov, Kirill K. St. Petersburg State Electrotechnical University 'LETI' Department of Robotics and Automation of Production Systems Saint Petersburg Russia Petersburg State University of Industrial Technologies and Design Department of Automated Electric Drive and Electrical Engineering Saint Saint Petersburg Russia

The types of errors of machine tools are considered. Methods for increasing the productivity of machine tools and the accuracy of processing workpieces are analyzed. Promising directions for the development of electri... 详细信息

ISBN: (纸本)9798350360646

关键词： automation control systems electric drives metalworking machines

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Reduction of THD Using Controlled Inverter for EV Motors

Reduction of THD Using Controlled Inverter for EV Motors

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Advances in Renewable Energy & Electric Vehicles (AREEV), International Conference on

作者： Anusha C Yankanchi Nalini Karchi Rakesh P Tapaskar Department of Electrical and Electronics KLE Technological University India Department of Automation and Robotics KLE Technological University Hubballi India

ISBN: (数字)9798331529574

ISBN: (纸本)9798331529581

The rapid proliferation of electric vehicles (EVs) has intensified the demand for advanced power electronics systems capable of delivering high efficiency, reliability, and compliance with stringent standards. Inverters, as a critical component in EV powertrains, perform the essential function of converting direct current (DC) from batteries into alternating current (AC) to drive motors. However, conventional inverters often suffer from significant Total Harmonic Distortion (THD), which adversely impacts motor efficiency, exacerbates thermal and electromagnetic stress, and diminishes the overall lifespan of the system. Addressing these challenges, this study introduces an enhanced inverter control strategy combining Sinusoidal Pulse Width Modulation (SPWM) with a Proportional-Integral (PI) controller, specifically optimized to reduce THD and improve system performance under dynamic conditions. The proposed methodology leverages SPWM for high-precision modulation of inverter switches, ensuring smooth and efficient power conversion. The inclusion of a PI controller facilitates real-time adjustment of voltage and frequency, maintaining a constant voltage-to-frequency ratio critical for minimizing harmonic content and ensuring stable motor operation. The controller parameters are meticulously tuned using the Ziegler-Nichols method, achieving optimal proportional and integral gains tailored for dynamic load variations. A comprehensive simulation framework is developed in MATLAB/Simulink, incorporating key EV powertrain components such as a multilevel inverter, a three-phase induction motor, and variable load profiles to emulate real-world conditions. Simulation results demonstrate a significant reduction in THD, from an initial 21.18% without control to a mere 0.49% with the proposed SPWM-PI controller, surpassing the IEEE 519 harmonic standard requirements. Furthermore, the system exhibits improved motor speed regulation, enhanced torque stability, and superior power qu

关键词： PI control Prevention and mitigation Mechanical power transmission Harmonic analysis Motors Electric vehicles Real-time systems Power conversion Vehicle dynamics Voltage control

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Denoising of Speech Signal using Deep Learning

Denoising of Speech Signal using Deep Learning

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2024 IEEE International Conference on Intelligent Systems and Advanced Applications, ICISAA 2024

作者： Wani, Priyanka Uttarwar, Sudhanshu Mote, Abhijeet Dada Chandan, M.N. Katarwar, Vandana Dr. D. Y. Patil Institute of Technology SPPU Department of Electronics and Telecommunication Pune India Mountain Digital TX United States JSPM's Rajashri Shahu College of Engineering Department of Automation and Robotics Pune India

ISBN: (纸本)9798331539948

Speech is the primary vocalized form of natural speech. Speaking is simple, hands-free, quick, and doesn't require any technological expertise. Speech recognition software makes it easy and comfortable for people to communicate with computers. A speech recognition system enabled this. Speech denoising using deep learning involves using neural networks to eliminate destortion from input signals, preserving the clarity of the speech. For this task, deep learning models such as CNNs or RNNs are commonly used. © 2024 IEEE.

关键词： Signal denoising

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